We present a new technique for using samples to estimate join cardinalities. This technique, which we term "end-biased samples," is inspired by recent work in network tr...
We propose a more efficient version of the slice sampler for Dirichlet process mixture models described by Walker (2007). This sampler allows the fitting of infinite mixture mod...
Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...
Two major stages stages in language identification systems can be identified: the language modeling stage, where the distinctive features of languages are determined and stored in...
Computational diagnosis of cancer is a classification problem, and it has two special requirements on a learning algorithm: perfect accuracy and small number of features used in t...